Antenna Season Report Notebook¶

Josh Dillon, Last Revised January 2022

This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.

In [1]:
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
In [2]:
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
In [3]:
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "185"
csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
In [4]:
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))

Antenna 185 Report

In [5]:
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
In [6]:
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 34 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_
Found 32 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
In [7]:
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'

Load relevant info from summary CSVs¶

In [8]:
this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
            antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
        else:
            antnum = int(row['Ant'])
        if antnum != int(antenna):
            continue
        
        if np.issubdtype(type(row['Node']), np.integer):
            row['Node'] = str(row['Node'])
        if type(row['Node']) == str and row['Node'].isnumeric():
            row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break
In [9]:
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])

Table 1: Per-Night RTP Summary Info For This Atenna¶

This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.

In [10]:
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))

Antenna 185, Node N14:

Out[10]:
JDs A Priori Status Auto Metrics Flags Dead Fraction in Ant Metrics (Jee) Dead Fraction in Ant Metrics (Jnn) Crossed Fraction in Ant Metrics Flag Fraction Before Redcal Flagged By Redcal chi^2 Fraction ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score Average Dead Ant Metric (Jee) Average Dead Ant Metric (Jnn) Average Crossed Ant Metric Median chi^2 Per Antenna (Jee) Median chi^2 Per Antenna (Jnn)
2459849 digital_ok 0.00% 0.00% 0.00% 0.00% 16.67% 0.00% 0.546675 -0.875016 2.137093 0.522666 -1.235328 -1.216863 0.013531 -0.994943 0.7582 0.7530 0.3541 1.529687 1.417095
2459848 digital_ok 0.00% 0.00% 0.00% 0.00% 30.15% 0.00% 0.807713 -0.482397 1.820739 -0.705173 -1.121419 -1.153705 -0.150808 -1.133030 0.7365 0.7542 0.3741 1.433439 1.378349
2459847 digital_ok 0.00% 0.00% 0.00% 0.00% 3.21% 0.00% 1.127335 -0.312815 1.359488 -0.672538 0.555282 -1.023784 0.133898 -0.261080 0.7405 0.6911 0.4289 1.660603 1.467075
2459846 digital_ok 0.00% 0.00% 0.00% 0.00% 33.33% 0.00% -0.456652 -0.579379 0.813639 -0.765152 -0.403107 -0.467929 -0.532771 -0.894398 0.8306 0.6647 0.4987 1.803902 1.478754
2459845 digital_ok 0.00% 0.00% 0.00% 0.00% 16.02% 83.98% 1.327739 -0.259134 2.742575 -0.936403 -1.271866 -1.092047 -0.375717 0.680048 0.7409 0.7424 0.3836 9.669439 8.079166
2459844 digital_ok 0.00% 100.00% 100.00% 0.00% - - 0.965217 -0.693858 -0.592447 -0.614068 -0.697116 -0.430245 -0.490779 -0.112899 0.0286 0.0266 0.0010 nan nan
2459843 digital_ok 0.00% 1.20% 0.66% 0.00% 15.22% 0.00% 0.403223 0.138672 0.650716 1.106558 -0.489396 0.531143 -0.714726 0.297312 0.7503 0.7401 0.3975 1.591305 1.526328
2459842 digital_ok 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.469007 -0.291197 -0.791839 1.456870 0.211284 0.449234 -0.078412 0.286913 0.7697 0.6806 0.2565 2.113511 2.035456
2459841 digital_ok 100.00% 100.00% 100.00% 0.00% - - 2.775188 1.226846 -0.597349 0.679478 19.737633 -0.730763 1.414063 1.226893 0.0287 0.0261 0.0017 nan nan
2459840 digital_ok 100.00% 100.00% 100.00% 0.00% - - 243.569197 173.808059 84.238685 86.357512 1022.419072 1239.804010 1994.363387 2319.178674 0.0205 0.0173 0.0019 nan nan
2459839 digital_ok 0.00% - - - - - -0.432887 -1.058488 0.285024 -0.795701 -0.566462 -0.856324 0.024711 -0.788475 nan nan nan nan nan
2459838 digital_ok 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.886871 -0.667757 1.306454 0.568953 -1.212704 0.398609 1.183186 -0.752675 0.7639 0.7149 0.4023 2.083487 1.884416
2459835 digital_ok 100.00% 100.00% 100.00% 0.00% - - 0.471252 -0.928180 0.650005 -1.171660 44.510791 34.414444 225.090979 179.382071 0.0370 0.0427 0.0013 nan nan
2459833 digital_ok 100.00% 100.00% 100.00% 0.00% - - 0.054299 -0.868819 -0.978100 -0.218658 63.798188 50.498225 228.738524 183.232228 0.0300 0.0286 0.0009 nan nan
2459832 digital_ok 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 1.753599 0.054326 0.686567 0.256512 -0.499348 -1.352254 3.518121 -0.938957 0.8114 0.5393 0.5857 1.716338 1.639485
2459831 digital_ok 0.00% 100.00% 100.00% 0.00% - - -0.358961 -0.834198 0.047247 -0.822877 -1.166412 -1.306100 -0.016924 -0.432625 0.0297 0.0275 0.0012 nan nan
2459830 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 1.170402 0.137348 1.478453 0.742352 -0.832390 -1.194556 9.674827 -1.039045 0.8100 0.5504 0.5771 6.311408 5.546154
2459829 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 1.419630 -0.171169 1.229882 0.907525 -1.232141 -1.117167 24.191036 -0.876092 0.7645 0.6767 0.4178 13.515691 14.847181
2459828 digital_ok 0.00% 0.00% 0.00% 0.00% 100.00% 0.00% 1.058343 0.153472 1.826197 1.230667 0.170742 -0.519980 -0.026722 -0.744512 0.8080 0.5625 0.5517 0.000000 0.000000
2459827 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 0.080354 0.023914 0.009468 1.188891 23.694440 -0.659221 4.866161 4.612245 0.7765 0.6909 0.4081 0.000000 0.000000
2459826 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 0.416993 0.246281 1.412345 0.855555 -0.094568 -0.333808 40.395364 -0.701874 0.8064 0.5940 0.5108 0.000000 0.000000
2459825 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% -0.087182 0.174708 6.976654 1.078551 3.851301 3.446951 9.080563 2.026399 0.7990 0.6044 0.5074 5.309364 5.709149
2459824 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% -0.152675 -0.383861 5.389198 0.969771 18.705926 0.496632 13.189062 2.264257 0.7302 0.7459 0.3585 3.540722 4.254506
2459823 digital_ok 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.287174 0.169959 1.046617 0.880321 -0.461142 1.249323 1.170286 -0.308928 0.7775 0.6573 0.4542 2.656774 2.766368
2459822 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 0.893616 0.253119 1.192622 1.193590 -0.559096 -0.262099 1.295101 4.339682 0.8124 0.6293 0.5022 4.313038 3.920356
2459821 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 0.726201 0.005011 2.400320 1.060728 0.885007 0.708647 -0.149530 4.884297 0.7980 0.6266 0.5097 3.937090 4.205261
2459820 digital_ok 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 1.094351 0.190205 2.449308 1.164057 -0.408823 -0.211886 0.353883 -1.224053 0.7888 0.6907 0.4180 2.016108 1.784415
2459817 digital_ok 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.958231 0.076846 0.329357 0.996510 3.019987 1.192519 0.920917 0.676354 0.8034 0.6556 0.5091 1.958369 1.742989
2459816 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 1.598812 0.412561 1.032743 1.383686 -0.373131 0.917810 5.083744 -0.677993 0.8458 0.6051 0.5809 4.444794 4.172289
2459815 digital_ok 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.746553 0.491522 0.980881 0.996544 -0.079801 0.646272 2.917438 -0.529572 0.7936 0.6622 0.5164 2.146286 1.839843
2459814 digital_ok 0.00% - - - - - nan nan nan nan nan nan nan nan nan nan nan nan nan
2459813 digital_ok 0.00% 0.00% 0.00% 0.00% 0.53% 0.00% 2.139036 0.390880 1.164625 0.485230 -0.517206 -0.031750 1.552447 -0.991701 0.7945 0.6923 0.4193 3.342429 2.415054

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

In [11]:
htmls_to_display = []
for am_html in auto_metric_htmls:
    html_to_display = ''
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line:
            htmls_to_display.append(html_to_display)
            break

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.

In [12]:
for i, html_to_display in enumerate(htmls_to_display):
    if i == 100:
        break
    display(HTML(html_to_display))

Antenna 185: 2459849

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
185 N14 digital_ok ee Power 2.137093 0.546675 -0.875016 2.137093 0.522666 -1.235328 -1.216863 0.013531 -0.994943

Antenna 185: 2459848

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
185 N14 digital_ok ee Power 1.820739 -0.482397 0.807713 -0.705173 1.820739 -1.153705 -1.121419 -1.133030 -0.150808

Antenna 185: 2459847

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
185 N14 digital_ok ee Power 1.359488 -0.312815 1.127335 -0.672538 1.359488 -1.023784 0.555282 -0.261080 0.133898

Antenna 185: 2459846

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
185 N14 digital_ok ee Power 0.813639 -0.456652 -0.579379 0.813639 -0.765152 -0.403107 -0.467929 -0.532771 -0.894398

Antenna 185: 2459845

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
185 N14 digital_ok ee Power 2.742575 -0.259134 1.327739 -0.936403 2.742575 -1.092047 -1.271866 0.680048 -0.375717

Antenna 185: 2459844

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
185 N14 digital_ok ee Shape 0.965217 0.965217 -0.693858 -0.592447 -0.614068 -0.697116 -0.430245 -0.490779 -0.112899

Antenna 185: 2459843

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
185 N14 digital_ok nn Power 1.106558 0.138672 0.403223 1.106558 0.650716 0.531143 -0.489396 0.297312 -0.714726

Antenna 185: 2459842

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
185 N14 digital_ok nn Power 1.456870 0.469007 -0.291197 -0.791839 1.456870 0.211284 0.449234 -0.078412 0.286913

Antenna 185: 2459841

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
185 N14 digital_ok ee Temporal Variability 19.737633 2.775188 1.226846 -0.597349 0.679478 19.737633 -0.730763 1.414063 1.226893

Antenna 185: 2459840

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
185 N14 digital_ok nn Temporal Discontinuties 2319.178674 243.569197 173.808059 84.238685 86.357512 1022.419072 1239.804010 1994.363387 2319.178674

Antenna 185: 2459839

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
185 N14 digital_ok ee Power 0.285024 -1.058488 -0.432887 -0.795701 0.285024 -0.856324 -0.566462 -0.788475 0.024711

Antenna 185: 2459838

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
185 N14 digital_ok ee Power 1.306454 -0.667757 0.886871 0.568953 1.306454 0.398609 -1.212704 -0.752675 1.183186

Antenna 185: 2459835

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
185 N14 digital_ok ee Temporal Discontinuties 225.090979 -0.928180 0.471252 -1.171660 0.650005 34.414444 44.510791 179.382071 225.090979

Antenna 185: 2459833

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
185 N14 digital_ok ee Temporal Discontinuties 228.738524 -0.868819 0.054299 -0.218658 -0.978100 50.498225 63.798188 183.232228 228.738524

Antenna 185: 2459832

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
185 N14 digital_ok ee Temporal Discontinuties 3.518121 1.753599 0.054326 0.686567 0.256512 -0.499348 -1.352254 3.518121 -0.938957

Antenna 185: 2459831

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
185 N14 digital_ok ee Power 0.047247 -0.358961 -0.834198 0.047247 -0.822877 -1.166412 -1.306100 -0.016924 -0.432625

Antenna 185: 2459830

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
185 N14 digital_ok ee Temporal Discontinuties 9.674827 1.170402 0.137348 1.478453 0.742352 -0.832390 -1.194556 9.674827 -1.039045

Antenna 185: 2459829

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
185 N14 digital_ok ee Temporal Discontinuties 24.191036 -0.171169 1.419630 0.907525 1.229882 -1.117167 -1.232141 -0.876092 24.191036

Antenna 185: 2459828

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
185 N14 digital_ok ee Power 1.826197 0.153472 1.058343 1.230667 1.826197 -0.519980 0.170742 -0.744512 -0.026722

Antenna 185: 2459827

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
185 N14 digital_ok ee Temporal Variability 23.694440 0.080354 0.023914 0.009468 1.188891 23.694440 -0.659221 4.866161 4.612245

Antenna 185: 2459826

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
185 N14 digital_ok ee Temporal Discontinuties 40.395364 0.246281 0.416993 0.855555 1.412345 -0.333808 -0.094568 -0.701874 40.395364

Antenna 185: 2459825

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
185 N14 digital_ok ee Temporal Discontinuties 9.080563 0.174708 -0.087182 1.078551 6.976654 3.446951 3.851301 2.026399 9.080563

Antenna 185: 2459824

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
185 N14 digital_ok ee Temporal Variability 18.705926 -0.152675 -0.383861 5.389198 0.969771 18.705926 0.496632 13.189062 2.264257

Antenna 185: 2459823

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
185 N14 digital_ok nn Temporal Variability 1.249323 0.169959 0.287174 0.880321 1.046617 1.249323 -0.461142 -0.308928 1.170286

Antenna 185: 2459822

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
185 N14 digital_ok nn Temporal Discontinuties 4.339682 0.893616 0.253119 1.192622 1.193590 -0.559096 -0.262099 1.295101 4.339682

Antenna 185: 2459821

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
185 N14 digital_ok nn Temporal Discontinuties 4.884297 0.005011 0.726201 1.060728 2.400320 0.708647 0.885007 4.884297 -0.149530

Antenna 185: 2459820

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
185 N14 digital_ok ee Power 2.449308 1.094351 0.190205 2.449308 1.164057 -0.408823 -0.211886 0.353883 -1.224053

Antenna 185: 2459817

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
185 N14 digital_ok ee Temporal Variability 3.019987 0.958231 0.076846 0.329357 0.996510 3.019987 1.192519 0.920917 0.676354

Antenna 185: 2459816

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
185 N14 digital_ok ee Temporal Discontinuties 5.083744 0.412561 1.598812 1.383686 1.032743 0.917810 -0.373131 -0.677993 5.083744

Antenna 185: 2459815

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
185 N14 digital_ok ee Temporal Discontinuties 2.917438 0.491522 0.746553 0.996544 0.980881 0.646272 -0.079801 -0.529572 2.917438

Antenna 185: 2459814

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
185 N14 digital_ok nn Shape nan nan nan nan nan nan nan nan nan

Antenna 185: 2459813

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
185 N14 digital_ok ee Shape 2.139036 0.390880 2.139036 0.485230 1.164625 -0.031750 -0.517206 -0.991701 1.552447
In [ ]: